A machine-driven process for human limb length estimation using inertial sensors

Abstract

The computer based human motion tracking systems are widely used in medicine and sports. The accurate determination of limb lengths is crucial for not only constructing the limb motion trajectories which are used for evaluation process of human kinematics, but also individually recognising human beings. Yet, as the common practice, the limb lengths are measured manually which is inconvenient, time-consuming and requires professional knowledge. In this paper, the estimation process of limb lengths is automated with a novel algorithm calculating curvature using the measurements from inertial sensors. The proposed algorithm was validated with computer simulations and experiments conducted with four healthy subjects. The experiment results show the significantly low root mean squared error percentages such as upper arm - 5.16%, upper limbs - 5.09%, upper leg - 2.56% and lower extremities - 6.64% compared to measured lengths.